Test characteristics of milk amyloid A ELISA, somatic cell count, and bacteriological culture for detection of intramammary pathogens that cause subclinical mastitis

A Rapid and Inexpensive PCR Test for Mastitis Diagnosis Based on NGS Data

Mastitis is a common mammary gland disease of dairy cattle caused by a wide range of organisms including bacteria, fungi and algae. Mastitis contributes to economic losses of dairy farms due to reduced yield and poor quality of milk. Since the correct identification of pathogens responsible for the development of mastitis is crucial to the success of treatment, it is necessary to develop a quick and accurate test to distinguish the main pathogens causing this disease. In this paper, we describe the development of a test based on the multiplex polymerase chain reaction (PCR) method allowing for the identification of Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis and Staphylococcus aureus. When creating our test, we relied on the results from new generation sequencing (NGS) for accurate determination of species affiliation. The multiplex PCR test was verified on 100 strains including veterinary samples, ATCC and Polish Collection of Microorganisms (PCM) reference strains. The obtained results indicate that this test is accurate and displays high specificity. It may serve as a valuable molecular tool for the detection of major mastitis pathogens.

[Investigations of a controlled, decision tree based procedure for Selective Dry Cow Treatment in Bavarian dairy farms]

OBJECTIVE

Four parameters of a decision tree for Selective Dry Cow Treatment (SDCT), examined in a previous study, were analyzed regarding their efficacy in detecting cows for dry cow treatment (DCT, use of intramammary antimicrobials). This study set out to review wether all parameters (somatic cell count [SCC≥ 200 000 SC/ml 3 months' milk yield recordings prior dry off (DO)], clinical mastitis history during lactation [≥1 CM], culturing [14d prior DO, detection of major pathogens] and California-Mastitis-Test [CMT, > rate 1/+ at DO]) are necessary for accurate decision making, whether there are possible alternatives to replace culturing, and whether a simplified model could replace the decision tree.

MATERIAL AND METHODS

Records of 18 Bavarian dairy farms from June 2015 to August 2017 were processed. Data analysis was carried out by means of descriptive statistics, as well as employing a binary cost sensitive classification tree and logit-models. For statistical analyses the outcomes of the full 4-parameter decision tree were taken as ground truth.

RESULTS

848 drying off procedures in 739 dairy cows (CDO) were included. SCC and CMT selected 88.1%, in combination with CM 95.6% of the cows that received DCT (n=494). Without culturing, 22 (4.4%) with major pathogens (8x Staphylococcus [S.] aureus) infected CDO would have been misclassified as not needing DCT. The average of geometric mean SCC (within 100 d prior DO) for CDO with negative results in culturing was<100 000 SC/ml milk, 100 000-150 000 SC/ml for CDO infected with minor pathogens, and ≥ 150 000 SC/ml for CDO infected with major pathogens (excluding S.aureus). Using SCC during lactation (at least 1x > 200 000 SC/ml) and positive CMT to select CDO for DCT, contrary to the decision tree, 37 CDO (4.4%) would have been treated "incorrectly without" and 43 CDO (5.1%) "unnecessarily with" DCT. Modifications were identified, such as SCC<131 000 SC/ml within 100 d prior to DO for detecting CDO with no growth or minor pathogens in culturing. The best model for grading CDO for or against DCT (CDO without CM and SCC<200 000 SC/ml [last 3 months prior DO]) had metrics of AUC=0.74, Accuracy=0.778, balanced Accuracy=0.63, Sensitivity=0.92 and Specificity=0.33.

CONCLUSIONS

Combining the decision tree's parameters SCC, CMT and CM renders suitable selection criteria under the conditions of this study. When omitting culturing, lower thresholds for SCC should be considered for each farm individually to select CDO for DCT. Nonetheless, the most accurate model could not replace the full decision tree.

Gut dysbiosis induces the development of mastitis through a reduction in host anti-inflammatory enzyme activity by endotoxemia

BACKGROUND

Mounting experimental evidence has shown that the gut microbiota plays a significant role in the pathogenesis of mastitis, and clinical investigations have found that the occurrence of mastitis is correlated with ruminal dysbiosis. However, the underlying mechanism by which the ruminal microbiota participates in the development of mastitis remains unknown.

RESULTS

In the present study, we found that cows with clinical mastitis had marked systemic inflammation, which was associated with significant ruminal dysbiosis, especially enriched Proteobacteria in the rumen. Ruminal microbiota transplantation from mastitis cows (M-RMT) to mice induced mastitis symptoms in recipient mice along with increased mammary proinflammatory signature activation of the TLR4-cGAS-STING-NF-κB/NLRP3 pathways. M-RMT also induced mucosal inflammation and impaired intestinal barrier integrity, leading to increased endotoxemia and systemic inflammation. Moreover, we showed that M-RMT mirrored ruminal microbiota disruption in the gut of recipient mice, as evidenced by enriched Proteobacteria and similar bacterial functions, which were correlated with most proinflammatory parameters and serum lipopolysaccharide (LPS) levels in mice. Recurrent low-grade LPS treatment mirrored gut dysbiosis-induced endotoxemia and caused severe mastitis in mice. Furthermore, we found that gut dysbiosis-derived LPS reduced host alkaline phosphatase activity by activating neuraminidase (Neu), which facilitates low-grade LPS exposure and E. coli-induced mastitis in mice. Conversely, treatment with calf intestinal alkaline phosphatase or the Neu inhibitor zanamivir alleviated low-grade LPS exposure and E. coli-induced mastitis in mice.

CONCLUSIONS

Our results suggest that ruminal dysbiosis-derived low-grade endotoxemia can cause mastitis and aggravate pathogen-induced mastitis by impairing host anti-inflammatory enzymes, which implies that regulating the ruminal or gut microbiota to prevent low-grade systemic inflammation is a potential strategy for mastitis intervention. Video Abstract.

Testing Two Somatic Cell Count Cutoff Values for Bovine Subclinical Mastitis Detection Based on Milk Microbiota and Peripheral Blood Leukocyte Transcriptome Profile

Somatic cell count (SCC) is an important indicator of the health state of bovine udders. However, the exact cut-off value used for differentiating the cows with healthy quarters from the cows with subclinical mastitis remains controversial. Here, we collected composite milk (milk from four udder quarters) and peripheral blood samples from individual cows in two different dairy farms and used 16S rRNA gene sequencing combined with RNA-seq to explore the differences in the milk microbial composition and transcriptome of cows with three different SCC levels (LSCC: <100,000 cells/mL, MSCC: 100,000−200,000 cells/mL, HSCC: >200,000 cells/mL). Results showed that the milk microbial profiles and gene expression profiles of samples derived from cows in the MSCC group were indeed relatively easily discriminated from those from cows in the LSCC group. Discriminative analysis also uncovered some differentially abundant microbiota at the genus level, such as Bifidobacterium and Lachnospiraceae_AC2044_group, which were more abundant in milk samples from cows with SCC below 100,000 cells/mL. As for the transcriptome profiling, 79 differentially expressed genes (DEGs) were found to have the same direction of regulation in two sites, and functional analyses also showed that biological processes involved in inflammatory responses were more active in MSCC and HSCC cows. Overall, these results showed a similarity between the milk microbiota and gene expression profiles of MSCC and HSCC cows, which presented further evidence that 100,000 cells/ml is a more optimal cut-off value than 200,000 cells/mL for intramammary infection detection at the cow level.

Milk proteins as mastitis markers in dairy ruminants - a systematic review

Mastitis is one of the most impacting diseases in dairy farming, and its sensitive and specific detection is therefore of the greatest importance. The clinical evaluation of udder and mammary secretions is typically combined with the milk Somatic Cell Count (SCC) and often accompanied by its bacteriological culture to identify the causative microorganism. In a constant search for improvement, several non-enzymatic milk proteins, including milk amyloid A (M-SAA), haptoglobin (HP), cathelicidin (CATH), and lactoferrin (LF), have been investigated as alternative biomarkers of mastitis for their relationship with mammary gland inflammation, and immunoassay techniques have been developed for detection with varying degrees of success. To provide a general overview of their implementation in the different dairy species, we carried out a systematic review of the scientific literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Our review question falls within the type “Diagnostic test accuracy questions” and aims at answering the diagnostic question: “Which are the diagnostic performances of mastitis protein biomarkers investigated by immunoassays in ruminant milk?”. Based on 13 keywords combined into 42 searches, 523 manuscripts were extracted from three scientific databases. Of these, 33 passed the duplicate removal, title, abstract, and full-text screening for conformity to the review question and document type: 78.8% investigated cows, 12.1% sheep, 9.1% goats, and 6.1% buffaloes (some included more than one dairy species). The most frequently mentioned protein was M-SAA (48.5%), followed by HP (27.3%), CATH (24.2%) and LF (21.2%). However, the large amount of heterogeneity among studies in terms of animal selection criteria (45.5%), index test (87.9%), and standard reference test (27.3%) resulted in a collection of data not amenable to meta-analysis, a common finding illustrating how important it is for case definitions and other criteria to be standardized between studies. Therefore, results are presented according to the SWiM (Synthesis Without Meta-analysis) guidelines. We summarize the main findings reported in the 33 selected articles for the different markers and report their results in form of comparative tables including sample selection criteria, marker values, and diagnostic performances, where available. Finally, we report the study limitations and bias assessment findings.

Evaluation and verification of the characteristic peptides for detection of Staphylococcus aureus in food by targeted LC-MS/MS

The traditional methods for detection of Staphylococcus aureus in food have some shortcomings, such as fussy operation and dependence on separation of pure colony. A novel strategy for detection of pathogenic bacteria bases on targeted analysis of the characteristic peptides by LC-MS/MS. The key to the success of this strategy is to identify a combination of reliable characteristic peptides that afford high specificity. In this study, the candidate characteristic peptides of S. aureus were evaluated bioformatically and then verified experimentally. UniProt protein database were used to perform BLAST analysis on the candidate characteristic peptides, and then their specificity were compared via targeted analysis in S. aureus and other Staphylococcus strains by LC-MS/MS. Finally, suitable S. aureus characteristic peptide was determined, by using which 100 cfu/mL S. aureus in milk samples were successfully detected, meeting the detection limit requirement in actual application. The results demonstrated the feasibility of the detection strategy of S. aureus based on characteristic peptides. The exploratory work is expected to promote the methodology research of food-borne pathogen inspection and further improve the inspection efficiency and quality.

Bayesian estimation of diagnostic accuracy of somatic cell counts history and on-farm milk culture using Petrifilm® to identify quarters or cows that should be treated with antimicrobials in selective treatment protocols at dry off

Bayesian latent class models were used to estimate the test accuracy (sensitivity (Se), specificity (Sp), and predictive values (NPV and PPV)) of cow-level somatic cell counts (SCC) data, quarter-level Petrifilm® on-farm milk culture, and quarter-level standard milk bacteriology for the identification of quarters that should possibly be treated with antimicrobials at dry off in dairy cows. Data of 282 cows from 9 dairy herds in Québec, Canada, with bulk tank SCC < 250,000 cells/mL were used. Estimated median herd-prevalence of infections that should be treated was 16.2 % (95 % credibility interval (CI): 11.0-22.7). Se and Sp estimates for quarter-milk culture using Petrifilm® were 82.2 % (95 %CI: 74.0-89.5) and 62.0 % (95 %CI: 58.6-65.6), respectively. Se and Sp for quarter-milk standard bacteriology were 67.4 % (95 %CI: 55.8-81.2) and 79.6 % (95 %CI: 76.4-83.0), respectively. Se and Sp of different SCC scenarios and thresholds were estimated. For first parity cows, using only the last Dairy Herd Improvement (DHI) test SCC with a threshold of 100,000 cells/mL appeared quite accurate, with Se, Sp, PPV, NPV and reduction of antimicrobial usage of 85.6 % (95 %CI: 69.6-95.6), 86.0 % (95 %CI: 80.0-91.7), 58.0 % (95 %CI: 42.3-74.2), 96.4 % (95 %CI: 91.3-99.0), and 75.3 % (95 %CI: 70.7-79.3), respectively. For cows of ≥ 2nd parity, using only the last DHI test SCC with a threshold of 200,000 cells/mL resulted in Se, Sp, PPV, NPV and reduction of antimicrobial usage of 75.3 % (95 %CI: 55.8-87.3), 84.0 % (95 %CI: 78.8-89.3), 47.2 % (95 %CI: 32.0-63.7), 94.7 % (95 %CI: 89.0-97.6), and of 77.0 % (95 %CI: 73.3-80.3), respectively. Adding quarter-level milk culture using Petrifilm® to cows identified as unhealthy using cow-level SCC data improved the test accuracy (mainly the PPV) and further reduced the use of antimicrobials. For instance, in ≥ 2nd parity cows, using only the last DHI SCC with a threshold of 200,000 cells/mL, adding a subsequent Petrifilm® test increased the reduction from 77.0 % (95 %CI: 73.3-80.3) to 89.5 % (95 %CI: 86.7-91.8). Considering the availability of SCC data, the easiness of using just the last DHI test, and the high NPV that could be achieved, producers may consider using just the last DHI test as a potential tool to identify cows that should be treated with antimicrobials at dry off. It may be used alone or in combination with quarter-level on-farm Petrifilm® milk culture on high SCC cows to further reduce the use of antimicrobials by identifying quarters that need to be treated.

The value of the biomarkers cathelicidin, milk amyloid A, and haptoglobin to diagnose and classify clinical and subclinical mastitis

Timely and objective diagnosis and classification of mastitis is crucial to ensure adequate management and therapeutic decisions. Analyzing specific biomarkers in milk could be advantageous compared with subjective or semiquantitative criteria, such as palpation of the udder in clinical mastitis cases or evaluation of somatic cell count using cow side tests (e.g., California Mastitis Test) in subclinical mastitis quarters. The objective of this study was to investigate the diagnostic value of 3 biomarkers; cathelicidin, milk amyloid A, and haptoglobin for the diagnosis of subclinical and clinical mastitis. Furthermore, the suitability of these biomarkers to differentiate between mild, moderate, and severe clinical mastitis and the influence of different pathogens on biomarker levels was tested. A total of 67 healthy cows, 119 cows with subclinical mastitis, and 212 cows with clinical mastitis were enrolled in the study. Although cathelicidin, haptoglobin, and milk amyloid A were measured in all samples from healthy cows and those with subclinical mastitis, haptoglobin, and cathelicidin results were only available from 121 out of 212 cows with clinical mastitis. Milk amyloid A was measured in all samples. In cows with clinical mastitis, the mastitic quarter and a second healthy quarter serving as a healthy in-cow control quarter were sampled. It was possible to differentiate between healthy quarters, quarters with subclinical mastitis, and quarters with clinical mastitis using all 3 biomarkers. Concerning cathelicidin, thresholds were 0.000 [sensitivity (Se) = 0.83, specificity (Sp) = 0.97] and 0.053 (Se = 0.98, Sp = 0.99) for normalized optical density at 450 nm (NOD450) for differentiating between healthy quarters and quarters with subclinical or clinical mastitis, respectively. Thresholds of 1.28 µg/mL (Se = 0.65, Sp = 0.76) and 1.81 µg/mL (Se = 0.77, Sp = 0.83) for milk amyloid A and 3.65 µg/mL (Se = 0.92, Sp = 0.94) and 5.40 µg/mL mL (Se = 0.96, Sp = 0.99) for haptoglobin were calculated, respectively. Healthy in-cow control quarters from cows with CM showed elevated milk amyloid A and haptoglobin levels compared with healthy quarters from healthy cows. Only the level of milk amyloid A was higher in severe clinical mastitis cases compared with mild ones. In contrast to clinical mastitis, cathelicidin and haptoglobin in subclinical mastitis quarters were significantly influenced by different bacteriological results. The measurement of cathelicidin, milk amyloid A, and haptoglobin in milk proved to be a reliable method to detect quarters with subclinical or clinical mastitis.

Rumen and Hindgut Bacteria Are Potential Indicators for Mastitis of Mid-Lactating Holstein Dairy Cows

Mastitis is one of the major problems for the productivity of dairy cows and its classifications have usually been based on milk somatic cell counts (SCCs). In this study, we investigated the differences in milk production, rumen fermentation parameters, and diversity and composition of rumen and hindgut bacteria in cows with similar SCCs with the aim to identify whether they can be potential microbial biomarkers to improve the diagnostics of mastitis. A total of 20 dairy cows with SCCs over 500 × 10³ cells/mL in milk but without clinical symptoms of mastitis were selected in this study. Random forest modeling revealed that Erysipelotrichaceae UCG 004 and the [Eubacterium] xylanophilum group in the rumen, as well as the Family XIII AD3011 group and Bacteroides in the hindgut, were the most influential candidates as key bacterial markers for differentiating "true" mastitis from cows with high SCCs. Mastitis statuses of 334 dairy cows were evaluated, and 96 in 101 cows with high SCCs were defined as healthy rather than mastitis according to the rumen bacteria. Our findings suggested that bacteria in the rumen and hindgut can be a new approach and provide an opportunity to reduce common errors in the detection of mastitis.

Facile construction of a molecularly imprinted polymer-based electrochemical sensor for the detection of milk amyloid A

A molecularly imprinted electrochemical sensor for the detection of serum amyloid A (MAA) in milk was established for early diagnosis of subclinical mastitis in dairy cows. The electrochemical sensor was initially constructed using a nanocomposite material (reduced graphene oxide/gold nanoparticles, AuNPs@rGO) to modify the working electrode. The template protein, MAA, was then immobilized using pyrrole as the functional monomer to carry out the electropolymerization. Finally, the template protein was removed to form a molecular imprint film with the capability to qualitatively and quantitatively signaling of MAA. Cyclic voltammetry (CV), differential pulse voltammetry (DPV), and scanning electron microscopy (SEM) were used to characterize the modification process of the molecularly imprinted electrochemical sensors. Under optimized conditions, the sensor shows two well-behaved linear relationships in the MAA concentration range 0.01 to 200 ng/mL. A lower detection limit was estimated to be 5 pg/mL (S/N = 3). Other parameters including the selectivity, reproducibility (RSD 3.2%), and recovery rate (96.1-103%) are all satisfactory. Compared with the traditional methods, detection of MAA to determine the subclinical mastitis of dairy cows can efficiently be diagnosed and hence prevent an outbreak of dairy cow mastitis. The electrochemical sensor can detect MAA more rapidly, sensitively, and inexpensively than the ELISA-based MAA detection. These advantages indicate that the method is promising for early diagnosis of dairy cows.

Technological interventions and advances in the diagnosis of intramammary infections in animals with emphasis on bovine population-a review

Mastitis, an inflammation of the udder, is a challenging problem in dairy animals accounting for high economic losses. Disease complexity, degree of economic losses and increasing importance of the dairy industries along with public health concerns envisages devising appropriate diagnostics of mastitis, which can offer rapid, accurate and confirmatory diagnosis. The various diagnostic tests of mastitis have been divided into general or phenotypic and specific or genotypic tests. General or phenotypic tests are those that identify general alterations, which are not specific to any pathogen. Genotypic tests are specific, hence confirmatory for diagnosis of mastitis and include specific culture, polymerase chain reaction (PCR) and its various versions (e.g. qRT-PCR), loop-mediated isothermal amplification, lateral flow assays, nucleotide sequencing, matrix-assisted laser desorption ionization time-of-flight mass spectrometry, and other molecular diagnostic methods. However, for highly specific and confirmatory diagnosis, pure cultures still provide raw materials for more sophisticated diagnostic technological interventions like PCR and nucleotide sequencing. Diagnostic ability of like infra-red thermography (IRT) has been shown to be similar to California mastitis test and also differentiates clinical mastitis from subclinical mastitis cases. As such, IRT can become a convenient and portable diagnostic tool. Of note, magnetic nanoparticles-based colorimetric biosensor assay was developed by using for instance proteolytic activity of plasmin or anti-S. aureus antibody. Last but not least, microRNAs have been suggested to be potential biomarkers for diagnosing bovine mastitis. This review summarizes the various diagnostic tests available for detection of mastitis including diagnosis through general and specific technological interventions and advances.

Methods for Diagnosing Mastitis

A diagnosis of mastitis is based on clinical observations or direct/indirect measures of the inflammatory response to infection, whereas a diagnosis of an intramammary infection is based on identification of the infectious agent. Somatic cell count/somatic cell score are common diagnostic tests for the detection of subclinical mastitis. Culture and polymerase chain reaction can be useful in the diagnosis of an intramammary infection; however, both have their advantages and disadvantages. Diagnosing the bacterial agent causing the intramammary infection can help to determine treatment and prevention strategies on the farm, which in turn can help to reduce incidence and prevalence.